---
title: "Translingual Information Retrieval: A Comparative Evaluation"
authors:
  - "Jaime G. Carbonell"
  - "Yiming Yang"
  - "Robert E. Frederking"
  - "Ralf D. Brown"
  - "Yibing Geng"
  - "Danny Lee"
doi: ""
url: "https://ijcai.org/proceedings/1997/103"
pdf: "https://ijcai.org/proceedings/1997/0103.pdf"
venue: "Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence"
year: 1997
pages: "708-714"
track: "Information Retrieval"
keywords:
---

# Translingual Information Retrieval: A Comparative Evaluation

Jaime G. Carbonell, Yiming Yang, Robert E. Frederking, Ralf D. Brown, Yibing Geng, Danny Lee

*Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence*, pages 708-714.

## Abstract

Translingual information retrieval (TIR) consists of providing a query in one language and searchin g document collections in one or mor e different languages. This paper introduc es n ew TIR methods and reports on comparative TIR expe rim ents with these new methods and with previously reported ones in a realistic setting. Methods fall into two categories: query transl at ion based , and statistical-IR approaches establishing translingua l associations. The results show that using bilingual corpora for automated ext raction of term equivalences in context outperforms other m et hods. Translingual versions of the Generalized Vector Space Model (GVSM) an d Lat ent Semantic Indexing (LS I) perform relatively well, as does translingua l pseudo relevance feedback (PRF). All showed re lativ ely small performance loss between monolingual and translingual versions. Query translation based on a general machinereadable bilingual dictionary - heretofore the most popular m et hod - did not mat ch the performance of other, more sophisticated m ethod s. Also , the previous very high LSI r es ults in the literatur e were disconfirmed by more r ea listi c releva nc e- based evaluations.